Answers Healthcare Providers Need to 5 Burning AI Questions in Revenue Cycle Management

Answers Healthcare Providers Need to 5 Burning AI Questions in Revenue Cycle Management


Healthcare providers are looking for ways to improve the efficiency of their revenue cycle management (RCM). A solution on everyone’s radar is Artificial Intelligence (AI), a powerful tool that can help healthcare providers streamline and automate their billing processes while ensuring accuracy and data security. But with so much information available, it can be hard to know where to start.

Outlined below are five pressing AI questions in healthcare RCM that will help give providers what they need to make an informed decision about AI implementation. Whether you’re new to AI or a seasoned veteran, all the answers you need to make the most of AI in revenue cycle management are here.

What are the top impacts AI is making today?

As more healthcare providers look to invest in RCM technology to address their major challenges, AI-powered solutions can give them a range of benefits, from reducing claim denials, to increasing collections, and improving the entire process without disruption to existing workflow.

  • Impact 1: Improved accuracy in coding and billing

AI can help identify coding errors and inconsistencies, improving the accuracy of claims submission and reducing claim denials. This leads to a faster payment cycle, which can positively impact the revenue of healthcare providers. Providers can gain an estimated $9.5 billion by automating their claims.

  • Impact 2: Enhanced revenue optimization

AI algorithms can analyze data and identify trends that can help healthcare providers optimize their revenue cycle, such as identifying the most efficient payment channels or uncovering patterns in payer behavior. AI can also provide predictive insights to prevent avoidable denials and guidance on which denials to maximize reimbursement.

  • Impact 3: Streamlined administrative tasks

AI-powered tools can automate many of the administrative tasks associated with RCM, like patient registration, verifying patient eligibility, coding claims, claim submissions and claims denials. This can reduce the workload of administrative staff and free up their time to focus on higher-value tasks, claims and unrecognized revenue.

  • Impact 4: Improved patient experience

AI can also enhance the patient experience by streamlining the billing process, providing more accurate cost estimates, and offering personalized payment options. This can lead to greater patient satisfaction and loyalty for a health system.

Why are claim denials a persistent and growing problem?

The issues with revenue cycle management are becoming increasingly pressing and are having a direct impact on the amount of uncompensated care in the United States. Currently estimated to be a staggering $43 billion annuallythe problem is only growing due to issues such as staffing shortages, staff turnover and training, and constantly changing codes from payers.

A recent survey of provider organizations reveals that the rate of claim denials has been steadily increasing by 10-15% every year. This is due to issues occurring at every step of the patient’s financial journey – from scheduling and registration to coding, billing and collections.

The impact of this is far-reaching, and organizations are looking for innovative solutions to try and reduce their denials rate, such as investing in technology and tools to support staff in their daily tasks and help them to identify mistakes quickly. According to the same survey, nearly three out of four healthcare executives say that claims are denied between 5-15% of the time. This is where AI can make a major impact to reduce the burden of uncompensated care and ensure that organizations are able to operate effectively.

What is driving denials?

Survey respondents also highlighted a number of key factors driving denials, the top 5 being authorizations (48%), provider eligibility (42%), coding errors (42%), incorrect modifiers (37%), and missed submission deadlines (35%).

Despite the mounting pressures of this issue, innovative solutions to reduce denials and ultimately help to reduce the burden of uncompensated care are available. By investing in technology, and introducing customer-centric models to their processes, providers are taking the necessary steps to improve efficiency and the patient experience.

Are automation and AI yielding greater performance and efficiency?

Automation, especially combined with AI technology, is becoming increasingly important in the management of claims and denials in healthcare. This helps streamline and optimize the claims process, enabling providers to process large amounts of data quickly and accurately, in order to avoid potential issues that could lead to denials.

AI technology can also identify potential issues before they arise and make precise corrections or interventions. Health systems often pay more to correct data entered upstream than they do to ensure quality data is entered correctly the first time. In addition, AI can detect fraudulent claims and denials, leading to improved accuracy in claims processing and enhanced revenue cycle management. By leveraging automation and AI solutions, healthcare providers are able to gain valuable insights into their claims and denials data, resulting in improved financial performance and greater efficiency.

What is the best way to retain talent?

Initially seen as a potential risk, automation, AI, and machine learning are now being embraced as a way to combat staffing shortages and improve job satisfaction and most importantly — retain talent.

A survey of revenue cycle professionals revealed that more than half (53%) believe staff turnover and shortages are slowing down the claims and denials resubmission process. Forty percent are worried this could cause errors when verifying claims, 38% are not confident about the accuracy of information exchange during registration, and 48% state patient estimates are accurate only half the time or less. Thirty-three percent also worry that the No Surprises Act will cause further complications and negatively impact payor reimbursement.

It is no surprise, then, that 74% of hospital RCM executives prioritize reducing denials, and plan to invest in technology and innovative solutions to reduce friction and increase claims management efficiency. According to the survey, the most common causes of denials are insufficient data and analytics (62%), lack of automation (61%), lack of staff training (46%), lack of in-house expertise (44%), and dated technology (33%).

Health systems are now looking for both proactive and reactive solutions, as well as partners with healthcare data and workflow expertise. Proactive solutions include leveraging AI to identify claims with a high chance of being denied and analyzing claims adjudication per payer. Reactive insights can help direct human efforts toward claims with a higher chance of being paid, rather than those with a lower chance of being paid.

Perhaps even more critical, though, are solutions that can be easily adopted, that integrate into existing workflows and that provide health system-specific modeling that can adapt in real time to changes in payer reimbursement policies while delivering customized triggers that help staff identify and correct issues before claims are submitted.

The impact of denied claims on hospitals and their patients is undeniable. Thankfully, technology solutions are being implemented to reduce denials and maximize efficiency. Automation, AI, and machine learning can all be used to identify issues that lead to denials, streamline the patient billing process, reduce manual processes, and provide real-time data to quickly process claims. With these solutions, health systems can ensure their revenue cycle runs smoothly and efficiently while providing maximum returns.

Photo: sorbetto, Getty Images



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